Tetraplegia, aka quadriplegia, aka the loss of motor function throughout the body from the neck down, occurs when something – usually a traumatic injury, but not always – disrupts the link between the brain and the nervous system. Without that crucial connection to your limbs, your brain can no longer tell your limbs how to move around, leaving you with little to no control over what your body does or doesn’t do at any given point.
But researchers from the University of Texas at Austin have developed a pretty neat workaround. A tetraplegic person’s brain may not be able to communicate with their legs to move them about their environment – but it might pretty soon be able to talk directly to their wheelchair instead.
“Mind-controlled wheelchairs are an intriguing assistive mobility solution applicable in complete paralysis,” begins a new paper detailing the results. And in a development worthy of a sci-fi blockbuster, that’s exactly what the team did: “We demonstrate[d] that three tetraplegic spinal-cord injury users could be trained to operate a non-invasive, self-paced thought-controlled wheelchair and execute complex navigation tasks,” the authors explain.
It’s not the first time researchers have touted a thought-powered mobility aid – but this new version has a few advantages over its predecessors. Most previous projects, for example, have been “limited to single-session evaluation with able-bodied users,” the authors note, with brain-machine interfaces (BMIs) that rely on registering users’ reactions to stimuli.
In contrast, this mind-controlled chair was actually tested by the people it was designed for – definitely an advantage when you’re investigating an invention’s fitness for purpose – and it relies on a combination of robotic intelligence and brain activity specific to movement. And that last bit is important, at least if you want to be doing anything else while you’re zipping about in your futuristic tele-chair: it means that users can think about other things, or have a conversation, or get bored or tired, and not accidentally tell their chair to turn 18 degrees left and crash at full speed into a big display of corn cobs.
So, users were trained to move the chair by imagining moving their hands and feet. That may sound strange, since tetraplegia is marked by an inability to do exactly that – but remember, that’s not because the brain isn’t sending these messages, it’s just that they’re getting lost along the way. A device that could read brain activity – say, an EEG worn as a cap fitted with electrodes – would still be able to pick up those signals, and send them on to be interpreted as movement commands.
Add to this a series of sensors attached to the wheelchair, plus a nifty piece of software that could translate what they saw into information about the environment – sort of a failsafe against the chair trying to slam into a brick wall just because the user thought “turn right” – and you’ve got yourself a fully operational mind-controlled wheelchair.
“It works a lot like riding a horse,” said José del R. Millán, professor in the Cockrell School of Engineering’s Chandra Family Department of Electrical and Computer Engineering, who led the project, in a statement. “The rider can tell the horse to turn left or to go into a gate. But the horse will ultimately have to figure out the optimal way to carry out those commands.”
So, should we expect to see these Professor X-esque devices on the commercial market any time soon? Well, there are a few reasons for optimism: firstly, it doesn’t require any invasive procedures – just a cap and a training manual – and thanks to recent developments out of the same research groups, it uses EEG electrodes that are specifically designed to be used long-term without needing replacement. On top of that, the chairs were tested in cluttered, natural environments, so moving into real-world situations shouldn’t be too difficult.
“We demonstrated that the people who will actually be the end users of these types of devices are able to navigate in a natural environment with the assistance of a brain-machine interface,” added Millán, who is also a professor of neurology at UT Austin’s Dell Medical School.
Nevertheless, it goes without saying that this was a very small study: just three people, one of whom was not able to achieve what the authors call “high navigational performance”. All three were spinal cord injury patients, which limits the generalizability of the results to anyone with a different clinical profile.
And the BMI itself is not perfect: going forwards, rather than left or right, is specifically highlighted in the study as “a major limitation of the proposed BMI and a source of high workload for the user.” Exactly how high a workload, though, is not yet known, since the study didn’t include any feedback from users – that’s not a failure on the researchers’ part, it just wasn’t part of the study design in the first place.
In short, there’s still a lot of work to be done before you see these machines down at your local CVS. But until then, it’s still a pretty impressive and exciting piece of technology – and the researchers definitely think they’re onto a winner.
“To date, [this is] the most promising pathways towards fulfilling the translational promise of BMI,” they write.
“We postulate that this represents a critical advance towards home and clinical use of brain-controlled assistive mobility technology.”
The results can be found in the journal iScience.